Large-scale data processing may involve extracting data of interest from raw data in one or more datasets and processing it into a useful data product. A database analyst may seek to request information from a database but may be prevented from doing so by a lack of an ability to customize a database query. The database analyst may also be unable to distribute the processing of the query across a distributed computational environment, which may include one or more servers. The database analyst may be restricted to a limited set of queries that may limit the effectiveness of the analyst's ability to obtain information from the database. The analyst may therefore seek data inefficiently using an excessive number of queries. The data analyst may also be required to transfer the processed information of the database to a separate process to analyze the data. The database analyst may therefore be required to spend an excessive amount of time obtaining information, which may lead to a delay, an additional cost of the analyst's time, an additional time for a processor usage, and a greater possibility of incurring a human made error. As a result, the database analyst may ultimately fail to find a desired information.